The End Of SEO? How AI Is Reshaping Brand Discovery On The Web

For decades, businesses optimised their content to make their brands visible, until artificial intelligence (AI) unlocked fresh opportunities. 

Businesses began leveraging AI engines to grow their customer base organically. But the way to look for a brand on the Web kept changing with the evolving AI landscape. A pivot to Generative Engine Optimisation (GEO) from Search Engine Optimisation (SEO) is the latest in AI search. 

“It’s more precise, less cluttered, and far easier to reach the target,” said Dr Rajeev Sharma, VP and head of medical affairs at Tata 1mg. “AI search is reshaping discovery, and GEO is a key focus area for us this year.”

Buried within the $122 Bn fundraise by OpenAI last month to build an AI superapp was a concept slowly taking on with Google search and its ad programs. “Search usage has nearly tripled in a year, and our ads pilot reached more than $100 Mn in ARR in under six weeks,” read a post from the ChatGPT parent.

AI search – as it is called – is described by service providers as GEO or AEO (Answer Engine Optimisation). The names are yet to be known, but they have led to major changes to the very fabric of the internet. Publishers relying on search traffic have been gutted, and big chunks of the SEO industry have been wiped out.

Is this the end of the road for SEO? The shift to information-by-AI has unlocked lucrative opportunities for companies making the pivot to the internet’s new reality. In fact, a major ecommerce platform like Shopify has recently been vocal on enabling merchants to sell via AI chats. 

But, why? Because AI search tracks this shift in user behaviour. This is also why agentic commerce has been picking up pace, with companies like Razorpay trying to provide a seamless experience in converting discoveries to purchases.

Instead of scanning 10 links, the user asks a 20-word question and get a synthesised answer from AI chat interfaces like Gemini, ChatGPT and Claude. Google itself has accelerated this with AI Overviews. The result is a growing ‘zero-click’ search, where discovery takes place without any traffic.

Conductor, a technology company for marketers, analysed over 3.3 Bn sessions across all their data sources. AI traffic from LLMs and chatbots accounted for more than 35.7 Mn of this. This could be just 1.08% of it, however. The study highlighted that the conversion rate for AI referral traffic was almost double that of the usual. Put simply, users are more likely to make a purchase after going through a link from within AI than through traditional referral channels like social media or blog posts.

In this new paradigm, therefore, visibility is no longer about ranking. It’s about being remembered by AI systems and converting those into leads.

Rewriting The SEO Playbook 

For over two decades, search followed a predictable playbook: brands optimised for keywords, backlinks, and rankings to capture clicks. That model is being disrupted by the AI-driven interfaces that prioritise direct answers over lists of links. 

According to Samanyou Garg, founder and CEO of Writesonic, a platform that tracks AI search visibility, identifies competitive gaps, and executes content optimisation, the user behaviour has shifted from short queries to detailed, intent-rich prompts. “People want a synthesis. They don’t want to go through thousands of links anymore,” he said.

This shift is fundamentally altering discovery. AI systems no longer rely on traditional SEO signals like page rank and, instead, interpret intent, run multiple internal searches, and generate a single, synthesised response. As a result, a brand can rank highly on Google and still be excluded from AI-generated answers. At the same time, features like AI Overviews are accelerating answer-led discovery, reducing click-through behaviour and compressing the traditional search funnel.

The move from search engines to answer engines is also changing the optimisation pattern. If SEO was about ranking, this new paradigm is about recall.

Nayhrit B, who co-founded Gushwork, which builds AI marketing agents to help businesses generate inbound leads from AI search engines like ChatGPT, Gemini, Claude, and Perplexity, explained that visibility now depends on whether AI models have encountered and understood a brand’s content as authoritative for specific queries. 

“For Google, you optimise for a ranked list. For AI, you optimise for recall,” he said. This shifts focus from generic, high-volume content to precise, well-structured answers aligned with narrow user intent.

In practice, companies like Gushwork are analysing citation patterns across platforms such as ChatGPT and Perplexity AI to understand what gets surfaced. Third-party sources like Reddit or Wikipedia often carry more weight than owned content, pushing brands to rethink distribution. As a result, content strategies are evolving towards building “answer surfaces” and tracking metrics like AI visibility and traffic, which measure how often a brand is cited in AI-generated responses rather than clicked.

The Shift In Demand

The shift towards AI-driven search is fundamentally redefining the playbook for industries that historically relied on traditional SEO for growth and traffic. As Sharma of Tata 1mg pointed out, the industry is moving beyond simple keyword optimisation to a model where content must be structured and machine-readable to remain competitive. 

For businesses dependent on organic search for sales, it is no longer sufficient to produce high-quality, vetted material for human eyes alone; that data must now be architected so that Large Language Models can accurately interpret and surface it. 

Sharma believes this necessitated a shift to where technical SEO, content engineering, and external authority signals work in tandem to ensure that a brand’s expertise is not just visible, but is the primary source of truth utilised by the AI interfaces now mediating the path between consumers and products.

Travel aggregator MakeMyTrip, for instance, sees AI-led discovery fundamentally reshaping how the intent of the user is read and acted upon.

Raj Rishi Singh, chief marketing officer and chief business officer for Corporates, Flights and GCC, MakeMyTrip, said the discovery journey is no longer linear but conversational. “Conversational interfaces let users express multiple preferences at once, giving us sharper, more nuanced understanding of what they actually want.”

He said MakeMyTrip’s scale of 100 Mn users generates deep, intent-rich signals across the travel journey, enabling precise targeting. With Myra, its GenAI assistant, interactions are becoming more contextual and expressive, bringing more clarity to the understanding of the traveller’s preference.

Singh stressed that visibility is being redefined by AI search. “Visibility is less about ranking and more about being a trusted signal that AI models draw on when generating answers. The brands that invest in genuine understanding will outlast the ones optimising for yesterday’s search.”

One of the stark examples of the demand that reaffirms the importance was when IndiaMART decided to drag OpenAI to court in 2025, alleging that it was unfairly excluded from responses while showing competitors. The Calcutta High Court observed that this could cause reputational and commercial harm, treating AI-driven visibility as a real market force. IndiaMART argued such omission misleads the user, distorts competition, and relies improperly on USTR reports. 

Rise Of A New Startup Category 

With the rise of AI search, a new category of startups has emerged in the ecosystem. Sayak Sen, who founded LLMLab, which provides actionable insights to improve brand visibility in AI search, said that the complexity of AI systems makes this a fundamentally different problem from SEO. “Earlier, SEO had a playbook. Now every model behaves differently,” he pointed out.

AI models are non-deterministic, continuously evolving, and context-aware. This makes it difficult for brands to rely solely on internal teams or static tools. The market therefore pivoted to product-plus-service models that combine tracking, insights, and execution.

Startups are building across three layers: tracking where brands appear across AI platforms, generating insights into why competitors are being cited, and executing changes to improve visibility. Writesonic integrates these capabilities on a single platform, while LLMLab is building autonomous systems that generate and implement optimisation actions through AI agents.

Garg explained that unlike the SEO era, where tools like SEMrush and Ahrefs dominated as standalone analytics platforms, the GEO stack is evolving differently. He noted that traditional SEO tools are now trying to add AI capabilities, but they carry the legacy baggage built around PageRank-driven systems.

In contrast, the GEO-first platforms are being designed for AI-native workflows, combining tracking, exploration, and execution into a single loop, rather than acting as passive dashboards.

Global players like Profound, which recently raised $96 Mn at a valuation of $1 Bn, and Promptwatch are also gaining traction, while Indian startups like Gushwork and Writesonic are establishing an early presence. The next phase of this category is expected to move beyond dashboards towards fully autonomous systems that continuously optimise brand visibility.

The competitive intensity is also rising. Venture funding has accelerated in this space, and founders point to a narrow window of 12 to 18 months to build a defensible position before citation patterns stabilise across AI systems.

SEO remains a foundational layer of the internet. But, it is no longer sufficient on its own.

AI has introduced a discovery layer where decisions are made before users reach traditional search engines. In this environment, visibility is determined not by ranking positions, but by whether a brand is selected as the answer.

As discovery shifts from links to responses, the competitive landscape is being redefined. Brands that adapt to this shift early are likely to gain a structural advantage, while those that delay may find themselves competing in a crowded market.

[Edited by: Kumar Chatterjee]
[Creatives by: Abhyam Gusai]

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